Sample-size and Repetition Effects on the Prediction Accuracy of Time and Error-rate Models in Steering Tasks

• Item type: Journal(1)
• 公開日: 2024-02-15
• タイトル: Sample-size and Repetition Effects on the Prediction Accuracy of Time and Error-rate Models in Steering Tasks
• タイトル / 言語: en
• タイトル: Sample-size and Repetition Effects on the Prediction Accuracy of Time and Error-rate Models in Steering Tasks
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: [一般論文] Human performance modeling, steering law, sample size
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_6501
• 資源タイプ: journal article
• 著者所属: LY Corporation
• 著者所属(英): en
• 著者所属(英): LY Corporation
• 著者名: Shota, Yamanaka
• 著者名(英): Shota, Yamanaka
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: A previous study on target pointing has shown that the accuracy of performance models improves as the number of participants and clicks increases, but the task was limited to artificially simplified one-dimensional movements. Practical user interfaces often require more complex operations, and thus we examine the effects of the number of participants and task repetitions on the fit of existing models for path-steering tasks. Empirical results showed that the model for predicting movement times consistently fitted the data with high accuracy, even when the numbers of participants and repetitions were small. However, the model for predicting error rates was less accurate in terms of R2, MAE, and RMSE. Therefore, the benefit of recruiting numerous participants is relatively greater for the error-rate prediction model, which supports the previous study on target-pointing tasks.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.32(2024) (online); DOI http://dx.doi.org/10.2197/ipsjjip.32.247; ------------------------------
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: A previous study on target pointing has shown that the accuracy of performance models improves as the number of participants and clicks increases, but the task was limited to artificially simplified one-dimensional movements. Practical user interfaces often require more complex operations, and thus we examine the effects of the number of participants and task repetitions on the fit of existing models for path-steering tasks. Empirical results showed that the model for predicting movement times consistently fitted the data with high accuracy, even when the numbers of participants and repetitions were small. However, the model for predicting error rates was less accurate in terms of R2, MAE, and RMSE. Therefore, the benefit of recruiting numerous participants is relatively greater for the error-rate prediction model, which supports the previous study on target-pointing tasks.; ------------------------------; This is a preprint of an article intended for publication Journal of; Information Processing(JIP). This preprint should not be cited. This; article should be cited as: Journal of Information Processing Vol.32(2024) (online); DOI http://dx.doi.org/10.2197/ipsjjip.32.247; ------------------------------
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AN00116647
• 書誌情報: 情報処理学会論文誌; 巻 65, 号 2, 発行日 2024-02-15
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 1882-7764
• 公開者 / 言語: ja
• 公開者 / 出版者: 情報処理学会